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Golang Samber Ro

Samuel BertheCommunityCreated by samberDistributed by Samuel Berthe

  • Skill
  • Tool integration
  • Software development
  • MIT
  • No issues found

From the author

Reactive streams and event-driven programming in Golang using samber/ro — ReactiveX implementation with 150+ type-safe operators, cold/hot observables, 5 subject types (Publish, Behavior, Replay, Async, Unicast), declarative pipelines via Pipe, 40+ plugins (HTTP, cron, fsnotify, JSON, logging), automatic backpressure, error propagation, and Go context integration. Apply when using or adopting samber/ro, when the codebase imports github.com/samber/ro, or when building asynchronous event-driven pipelines, real-time data processing, streams, or reactive architectures in Go. Not for finite slice transforms (→ See `samber/cc-skills-golang@golang-samber-lo` skill).
— the description by samber

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

samber/ro is a Go implementation of ReactiveX that provides a type-safe, declarative approach to managing asynchronous data streams. It replaces complex, manual goroutine and channel wiring with a composable pipeline architecture. The library features over 150 operators, support for both cold and hot observables, automatic backpressure, and built-in error propagation. It is designed for scenarios involving infinite event streams, real-time data processing, and complex async coordination, offering a robust alternative to standard library concurrency primitives when declarative stream management is required.

What it does

  • Provides 150+ type-safe operators for transforming, filtering, and combining data streams.
  • Supports cold and hot observables for flexible event distribution and resource management.
  • Includes 40+ plugins for common tasks like HTTP, cron, logging, and file system monitoring.
  • Implements automatic backpressure and error propagation across pipeline stages.
  • Integrates natively with Go context for cancellation and timeout management.
  • Offers five subject types for advanced multicast and state-sharing patterns.

When to use it

  • When building infinite event-driven pipelines (e.g., WebSockets, tickers, file watchers).
  • When real-time data enrichment requires combining multiple asynchronous sources.
  • When you need declarative retry, timeout, or fallback logic for remote service calls.
  • When managing pub/sub patterns where multiple consumers share a single data source.
  • When standard goroutine/channel patterns become too verbose or difficult to maintain.

Advantages

  • Reduces boilerplate code compared to manual channel and goroutine management.
  • Enhances code readability through declarative, chainable pipeline operators.
  • Improves reliability with built-in error handling and context-aware cancellation.
  • Provides compile-time type safety via typed Pipe functions.
  • Simplifies complex async coordination like stream merging, zipping, and throttling.

Usage examples

“Create a reactive pipeline that filters even numbers from an interval stream and maps them to strings.”
The agent generates a Pipe2 chain using ro.RangeWithInterval, ro.Filter, and ro.Map, followed by a Subscribe call to handle the output.
“How do I implement a remote API call with retries and a timeout using samber/ro?”
The agent provides a pipeline using ro.Timeout and ro.RetryWithConfig to wrap the API call, ensuring robust execution.
“Show me how to share a single WebSocket stream between two different consumers.”
The agent demonstrates using ro.Share to convert a cold observable into a hot one, allowing multiple subscribers to receive the same events.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/samber/golang-samber-ro/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip golang-samber-ro.zip -d .agents/skills

Documentation by samber

Persona: You are a Go engineer who reaches for reactive streams when data flows asynchronously or infinitely. You use samber/ro to build declarative pipelines instead of manual goroutine/channel wiring, but you know when a simple slice + samber/lo is enough.

Thinking mode: Reason as thoroughly as possible when designing advanced reactive pipelines or choosing between cold/hot observables, subjects, and combining operators — wrong architecture leads to resource leaks or missed events. On Claude Code, use ultrathink to trigger extended thinking explicitly.

samber/ro — Reactive Streams for Go

Go implementation of ReactiveX. Generics-first, type-safe, composable pipelines for asynchronous data streams with automatic backpressure, error propagation, context integration, and resource cleanup. 150+ operators, 5 subject types, 40+ plugins.

Official Resources:

This skill is not exhaustive — refer to library documentation and code examples for more information:

  • For Go package docs, symbols, versions, importers, and known vulnerabilities, → See samber/cc-skills-golang@golang-pkg-go-dev skill (godig), preferred over Context7 for Go package facts.

  • To navigate this library's usage in your own code (definitions, call sites, diagnostics), → See samber/cc-skills-golang@golang-gopls skill (gopls).

  • Context7 remains a fallback for docs not indexed on pkg.go.dev.

Why samber/ro (Streams vs Slices)

Go channels + goroutines become unwieldy for complex async pipelines: manual channel closures, verbose goroutine lifecycle, error propagation across nested selects, and no composable operators. samber/ro solves this with declarative, chainable stream operators.

When to use which tool:

ScenarioToolWhy
Transform a slice (map, filter, reduce)samber/loFinite, synchronous, eager — no stream overhead needed
Simple goroutine fan-out with error handlingerrgroupStandard lib, lightweight, sufficient for bounded concurrency
Infinite event stream (WebSocket, tickers, file watcher)samber/roDeclarative pipeline with backpressure, retry, timeout, combine
Real-time data enrichment from multiple async sourcessamber/roCombineLatest/Zip compose dependent streams without manual select
Pub/sub with multiple consumers sharing one sourcesamber/roHot observables (Share/Subjects) handle multicast natively

Key differences: lo vs ro

Aspectsamber/losamber/ro
DataFinite slicesInfinite streams
ExecutionSynchronous, blockingAsynchronous, non-blocking
EvaluationEager (allocates intermediate slices)Lazy (processes items as they arrive)
TimingImmediateTime-aware (delay, throttle, interval, timeout)
Error modelReturn (T, error) per callError channel propagates through pipeline
Use caseCollection transformsEvent-driven, real-time, async pipelines

Installation

go get github.com/samber/ro

Core Concepts

Four building blocks:

  1. Observable — a data source that emits values over time. Cold by default: each subscriber triggers independent execution from scratch

  2. Observer — a consumer with three callbacks: onNext(T), onError(error), onComplete()

  3. Operator — a function that transforms an observable into another observable, chained via Pipe

  4. Subscription — the connection between observable and observer. Call .Wait() to block or .Unsubscribe() to cancel

observable := ro.Pipe2(
    ro.RangeWithInterval(0, 5, 1*time.Second),
    ro.Filter(func(x int) bool { return x%2 == 0 }),
    ro.Map(func(x int) string { return fmt.Sprintf("even-%d", x) }),
)

observable.Subscribe(ro.NewObserver(
    func(s string) { fmt.Println(s) },      // onNext
    func(err error) { log.Println(err) },    // onError
    func() { fmt.Println("Done!") },         // onComplete
))
// Output: "even-0", "even-2", "even-4", "Done!"

// Or collect synchronously:
values, err := ro.Collect(observable)

Cold vs Hot Observables

Cold (default): each .Subscribe() starts a new independent execution. Safe and predictable — use by default.

Hot: multiple subscribers share a single execution. Use when the source is expensive (WebSocket, DB poll) or subscribers must see the same events.

Convert withBehavior
Share()Cold → hot with reference counting. Last unsubscribe tears down
ShareReplay(n)Same as Share + buffers last N values for late subscribers
Connectable()Cold → hot, but waits for explicit .Connect() call
SubjectsNatively hot — call .Send(), .Error(), .Complete() directly
SubjectConstructorReplay behavior
PublishSubjectNewPublishSubject[T]()None — late subscribers miss past events
BehaviorSubjectNewBehaviorSubject[T](initial)Replays last value to new subscribers
ReplaySubjectNewReplaySubject[T](bufferSize)Replays last N values
AsyncSubjectNewAsyncSubject[T]()Emits only last value, only on complete
UnicastSubjectNewUnicastSubject[T](bufferSize)Single subscriber only

For subject details and hot observable patterns, see Subjects Guide.

Operator Quick Reference

CategoryKey operatorsPurpose
CreationJust, FromSlice, FromChannel, Range, Interval, Defer, FutureCreate observables from various sources
TransformMap, MapErr, FlatMap, Scan, Reduce, GroupByTransform or accumulate stream values
FilterFilter, Take, TakeLast, Skip, Distinct, Find, First, LastSelectively emit values
CombineMerge, Concat, Zip2–Zip6, CombineLatest2–CombineLatest5, RaceMerge multiple observables
ErrorCatch, OnErrorReturn, OnErrorResumeNextWith, Retry, RetryWithConfigRecover from errors
TimingDelay, DelayEach, Timeout, ThrottleTime, SampleTime, BufferWithTimeControl emission timing
Side effectTap/Do, TapOnNext, TapOnError, TapOnCompleteObserve without altering stream
TerminalCollect, ToSlice, ToChannel, ToMapConsume stream into Go types

Use typed Pipe2, Pipe3 ... Pipe25 for compile-time type safety across operator chains. The untyped Pipe uses any and loses type checking.

For the complete operator catalog (150+ operators with signatures), see Operators Guide.

Common Mistakes

MistakeWhy it failsFix
Using ro.OnNext() without error handlerErrors are silently dropped — bugs hide in productionUse ro.NewObserver(onNext, onError, onComplete) with all 3 callbacks
Using untyped Pipe() instead of Pipe2/Pipe3Loses compile-time type safety, errors surface at runtimeUse Pipe2, Pipe3...Pipe25 for typed operator chains
Forgetting .Unsubscribe() on infinite streamsGoroutine leak — the observable runs foreverUse TakeUntil(signal), context cancellation, or explicit Unsubscribe()
Using Share() when cold is sufficientUnnecessary complexity, harder to reason about lifecycleUse hot observables only when multiple consumers need the same stream
Using samber/ro for finite slice transformsStream overhead (goroutines, subscriptions) for a synchronous operationUse samber/lo — it's simpler, faster, and purpose-built for slices
Not propagating context for cancellationStreams ignore shutdown signals, causing resource leaks on terminationChain ContextWithTimeout or ThrowOnContextCancel in the pipeline

Best Practices

  1. Always handle all three events — use NewObserver(onNext, onError, onComplete), not just OnNext. Unhandled errors cause silent data loss

  2. Use Collect() for synchronous consumption — when the stream is finite and you need []T, Collect blocks until complete and returns the slice + error

  3. Prefer typed Pipe functions — Pipe2, Pipe3...Pipe25 catch type mismatches at compile time. Reserve untyped Pipe for dynamic operator chains

  4. Bound infinite streams — use Take(n), TakeUntil(signal), Timeout(d), or context cancellation. Unbounded streams leak goroutines

  5. Use Tap/Do for observability — log, trace, or meter emissions without altering the stream. Chain TapOnError for error monitoring

  6. Prefer samber/lo for simple transforms — if the data is a finite slice and you need Map/Filter/Reduce, use lo. Reach for ro when data arrives over time, from multiple sources, or needs retry/timeout/backpressure

Plugin Ecosystem

40+ plugins extend ro with domain-specific operators:

CategoryPluginsImport path prefix
EncodingJSON, CSV, Base64, Gobplugins/encoding/...
NetworkHTTP, I/O, FSNotifyplugins/http, plugins/io, plugins/fsnotify
SchedulingCron, ICSplugins/cron, plugins/ics
ObservabilityZap, Slog, Zerolog, Logrus, Sentry, Oopsplugins/observability/..., plugins/samber/oops
Rate limitingNative, Ululeplugins/ratelimit/...
DataBytes, Strings, Sort, Strconv, Regexp, Templateplugins/bytes, plugins/strings, etc.
SystemProcess, Signalplugins/proc, plugins/signal

For the full plugin catalog with import paths and usage examples, see Plugin Ecosystem.

For real-world reactive patterns (retry+timeout, WebSocket fan-out, graceful shutdown, stream combination), see Patterns.

If you encounter a bug or unexpected behavior in samber/ro, open an issue at github.com/samber/ro/issues.

Cross-References

  • → See samber/cc-skills-golang@golang-samber-lo skill for finite slice transforms (Map, Filter, Reduce, GroupBy) — use lo when data is already in a slice

  • → See samber/cc-skills-golang@golang-samber-mo skill for monadic types (Option, Result, Either) that compose with ro pipelines

  • → See samber/cc-skills-golang@golang-samber-hot skill for in-memory caching (also available as an ro plugin)

  • → See samber/cc-skills-golang@golang-concurrency skill for goroutine/channel patterns when reactive streams are overkill

  • → See samber/cc-skills-golang@golang-observability skill for monitoring reactive pipelines in production

Files

references/operators-guide.md

Operators Guide

samber/ro provides 150+ operators organized by category. All operators are generic functions that take and return Observable[T], designed for chaining via Pipe.

Table of Contents

  • Pipeline Construction

  • Creation Operators

  • Transformation Operators

  • Filtering Operators

  • Combining Operators

  • Math and Aggregation

  • Error Handling

  • Timing and Buffering

  • Side Effects (Tap / Do)

  • Connectable and Sharing

  • Context Operators

  • Conditional Operators

  • Terminal Operators

  • Observer and Subscription

  • Scheduling

  • Concurrency Modes

Pipeline Construction

// Typed pipes (Pipe1 through Pipe25) — compile-time type safety
result := ro.Pipe2(source, op1, op2)
result := ro.Pipe3(source, op1, op2, op3)

// Untyped pipe — uses any, loses type checking
result := ro.Pipe(source, op1, op2, op3)

// Reusable operator composition (curried)
transform := ro.PipeOp2(op1, op2) // returns func(Observable[A]) Observable[C]
result := transform(source)

// Synchronous collection
values, err := ro.Collect(observable)

Creation Operators

Create observables from various sources. Typically the first argument to Pipe.

OperatorSignaturePurpose
JustJust[T](values ...T) Observable[T]Emit specific values then complete
OfOf[T](values ...T) Observable[T]Alias for Just
FromSliceFromSlice[T](items []T) Observable[T]Create from existing slice
FromChannelFromChannel[T](ch <-chan T) Observable[T]Wrap Go channel as observable
RangeRange(start, end int) Observable[int]Emit integer sequence
RangeWithStepRangeWithStep(start, end, step int) Observable[int]Integer sequence with custom step
RangeWithIntervalRangeWithInterval(start, end int, d time.Duration) Observable[int]Integers with delay between each
RangeWithStepAndIntervalRangeWithStepAndInterval(start, end, step int, d time.Duration) Observable[int]Step + interval combined
IntervalInterval(d time.Duration) Observable[int64]Emit sequential integers at intervals (infinite)
IntervalWithInitialIntervalWithInitial(initial, d time.Duration) Observable[int64]Interval with initial delay
TimerTimer(d time.Duration) Observable[int64]Single emission after delay
RepeatRepeat[T](item T, count int64) Observable[T]Repeat item N times
RepeatWithIntervalRepeatWithInterval[T](item T, count int64, d time.Duration) Observable[T]Repeat with delay
DeferDefer[T](factory func() Observable[T]) Observable[T]Lazily create observable on subscription
FutureFuture[T](factory func() (T, error)) Observable[T]Single async value from function
StartStart(cb func() (any, error)) Observable[any]Execute callback and emit result
EmptyEmpty[T]() Observable[T]Complete immediately, no values
NeverNever[T]() Observable[T]Never emit or complete
ThrowThrow[T](err error) Observable[T]Immediately error
// Custom observable with direct control
obs := ro.NewObservable[int](func(ctx context.Context, observer ro.Observer[int]) error {
    observer.Next(1)
    observer.Next(2)
    observer.Complete()
    return nil
})

Transformation Operators

Transform each value in the stream.

OperatorPurpose
Map[T, R](fn func(T) R)Transform each value T -> R
MapI[T, R](fn func(T, int64) R)Map with index
MapErr[T, R](fn func(T) (R, error))Map that can fail — error propagates
MapWithContext[T, R](fn func(ctx, T) (ctx, R))Map with context access
MapTo[T, R](output R)Replace all values with a constant
FlatMap[T, R](fn func(T) Observable[R])Map each value to observable, flatten results
MergeMap[T, R](fn func(T) Observable[R])Alias for FlatMap
Scan[T, R](fn func(R, T) R, seed R)Running accumulation, emit each intermediate
Reduce[T, R](fn func(R, T) R, seed R)Accumulate, emit only final result
GroupBy[T, K](fn func(T) K)Partition into grouped observables by key
Cast[T, U]()Type cast values
Flatten[T]()Flatten Observable[[]T] to Observable[T]
Materialize[T]()Wrap values in Notification[T] (next/error/complete)
Dematerialize[T]()Unwrap Notification[T] back to values
Timestamp[T]()Emit TimestampValue[T] with emission time
TimeInterval[T]()Emit IntervalValue[T] with time since last emission
// FlatMap: for each user ID, fetch their orders (returns observable)
orders := ro.Pipe2(
    userIDs,
    ro.FlatMap(func(id int) ro.Observable[Order] {
        return fetchOrders(id)
    }),
    ro.Filter(func(o Order) bool { return o.Status == "paid" }),
)

// Scan: running sum
ro.Pipe1(
    ro.Just(1, 2, 3, 4, 5),
    ro.Scan(func(acc, x int) int { return acc + x }, 0),
)
// Emits: 1, 3, 6, 10, 15

Filtering Operators

Selectively emit values from the stream.

OperatorPurpose
Filter[T](fn func(T) bool)Emit only values matching predicate
FilterI[T](fn func(T, int64) bool)Filter with index
FilterWithContext[T](fn func(ctx, T) (ctx, bool))Filter with context access
Distinct[T comparable]()Emit only unique values
DistinctBy[T, K](fn func(T) K)Unique by key function
Take[T](n int64)Emit first N values then complete
TakeLast[T](n int)Emit last N values
TakeWhile[T](fn func(T) bool)Emit while predicate true, then complete
TakeUntil[T, S](signal Observable[S])Emit until signal observable emits
Skip[T](n int64)Skip first N values
SkipLast[T](n int)Skip last N values
SkipWhile[T](fn func(T) bool)Skip while predicate true
SkipUntil[T, S](signal Observable[S])Skip until signal emits
Head[T]()First item only
Tail[T]()All items except first
ElementAt[T](n int)Item at specific index
ElementAtOrDefault[T](n int64, fallback T)Item at index or default
Find[T](fn func(T) bool)First value matching predicate
First[T](fn func(T) bool)First matching value (alias-like)
Last[T](fn func(T) bool)Last matching value
Contains[T](fn func(T) bool)Emit bool: whether any value matches

All filtering operators have I (indexed), WithContext, and IWithContext variants.

Combining Operators

Merge multiple observables into one.

OperatorPurpose
Merge[T](sources ...Observable[T])Interleave emissions from all sources
MergeWith[T](obs ...Observable[T])Chainable merge
MergeAll[T]()Flatten Observable[Observable[T]] by merging
Concat[T](obs ...Observable[T])Sequential: complete first, then start second
ConcatWith[T](obs ...Observable[T])Chainable concat
ConcatAll[T]()Flatten by concatenating sequentially
Zip2[A, B](a, b)Pair values from 2 sources into lo.Tuple2
Zip3 ... Zip6Zip 3-6 sources into corresponding lo.Tuple
ZipWith[A, B](obsB)Chainable zip
CombineLatest2[A, B](a, b)Emit combined latest when either source emits
CombineLatest3 ... CombineLatest5Combine 3-5 sources
CombineLatestWith[A, B](obsB)Chainable combine-latest
Race[T](sources ...Observable[T])Emit from whichever source emits first
Amb[T](sources ...)Alias for Race
StartWith[T](prefixes ...T)Prepend values before source emissions
EndWith[T](suffixes ...T)Append values after source completes
// Zip: pair user with their settings
ro.Zip2(userStream, settingsStream)
// Emits: lo.Tuple2[User, Settings]

// CombineLatest: re-emit whenever either changes
ro.CombineLatest2(priceStream, quantityStream)
// Emits latest (price, quantity) pair each time either updates

Math and Aggregation

OperatorPurpose
Count[T]()Count of emitted values
Sum[T Numeric]()Sum of all values
Average[T Numeric]()Average as float64
Max[T Numeric]()Maximum value
Min[T Numeric]()Minimum value
Abs()Absolute value (float64)
Ceil() / Floor() / Round() / Trunc()Rounding (float64)
CeilWithPrecision(n) / FloorWithPrecision(n)Rounding with decimal places
Clamp[T](lower, upper)Constrain values to range

Error Handling

OperatorPurpose
Catch[T](fn func(error) Observable[T])Catch error, switch to recovery observable
OnErrorReturn[T](value T)Replace error with fallback value
OnErrorResumeNextWith[T](obs ...Observable[T])Continue with fallback observables on error
Retry[T]()Retry indefinitely on error
RetryWithConfig[T](cfg RetryConfig)Retry with max attempts, delay, backoff
ThrowIfEmpty[T](fn func() error)Error if stream completes empty
// RetryConfig for exponential backoff
ro.RetryWithConfig[Response](ro.RetryConfig{
    Max:               3,
    Delay:             time.Second,
    BackoffMultiplier: 2.0,
    MaxDelay:          10 * time.Second,
})

Timing and Buffering

OperatorPurpose
Delay[T](d time.Duration)Delay entire stream
DelayEach[T](d time.Duration)Delay between each emission
Timeout[T](d time.Duration)Error if no emission within duration
ThrottleTime[T](d time.Duration)Ignore values within duration of last
ThrottleWhen[T, t](tick Observable[t])Throttle by signal
SampleTime[T](d time.Duration)Emit latest value at intervals
SampleWhen[T, t](tick Observable[t])Sample by signal
BufferWithCount[T](n int)Collect N items, emit as []T
BufferWithTime[T](d time.Duration)Collect within time window
BufferWithTimeOrCount[T](n, d)Buffer with either condition
BufferWhen[T, B](boundary Observable[B])Buffer until signal
WindowWhen[T, B](boundary Observable[B])Window as nested observables
Pairwise[T]()Emit consecutive pairs

Side Effects (Tap / Do)

Execute code without changing the stream. Do is an alias for Tap.

OperatorPurpose
Tap[T](onNext, onError, onComplete)Side effect on all events
TapOnNext[T](fn func(T))Side effect on values
TapOnError[T](fn func(error))Side effect on errors
TapOnComplete[T](fn func())Side effect on completion
TapOnSubscribe[T](fn func())Side effect on subscription
TapOnFinalize[T](fn func())Side effect on teardown

All have WithContext variants. Do, DoOnNext, DoOnError, DoOnComplete, DoOnSubscribe, DoOnFinalize are aliases.

Connectable and Sharing

OperatorPurpose
Share[T]()Cold -> hot with reference counting
ShareWithConfig[T](cfg ShareConfig[T])Share with reset options
ShareReplay[T](bufferSize int)Share + replay last N values to late subscribers
ShareReplayWithConfig[T](n, cfg)ShareReplay with reset options
Serialize[T]()Queue emissions to ensure serial delivery
// ShareConfig controls lifecycle reset
ro.ShareConfig[T]{
    ResetOnComplete:       true,  // re-subscribe on complete
    ResetOnError:          true,  // re-subscribe on error
    ResetOnReferenceCount: true,  // re-subscribe when count drops to 0
}

Context Operators

OperatorPurpose
ContextReset[T](ctx context.Context)Replace pipeline context
ContextWithValue[T](key, value any)Add value to context
ContextWithTimeout[T](d time.Duration)Add timeout
ContextWithDeadline[T](t time.Time)Add deadline
ContextMap[T](fn func(ctx) ctx)Transform context
ThrowOnContextCancel[T]()Error when context is cancelled

Conditional Operators

OperatorPurpose
All[T](fn func(T) bool)Emit bool: whether all values match
DefaultIfEmpty[T](value T)Emit default if source completes empty
ThrowIfEmpty[T](fn func() error)Error if empty
Iif[T](pred func() bool, a, b Observable[T])Choose between two observables
While[T](cond func() bool)Repeat while condition true
DoWhile[T](cond func() bool)Execute at least once, repeat while true
SequenceEqual[T](obsB Observable[T])Emit bool: whether two streams match

Terminal Operators

OperatorPurpose
Collect[T](obs Observable[T]) ([]T, error)Block, return all values as slice
CollectWithContext[T](ctx, obs) ([]T, ctx, error)Collect with context
ToSlice[T]()Operator: emit []T on complete
ToChannel[T](size int)Convert to <-chan Notification[T]
ToMap[T, K, V](fn func(T) (K, V))Collect into map

Observer and Subscription

// Full observer (recommended)
observer := ro.NewObserver[T](onNext, onError, onComplete)

// Context-aware observer
observer := ro.NewObserverWithContext[T](onNext, onError, onComplete)

// Convenience shortcuts
observer := ro.OnNext[T](func(v T) { ... })
observer := ro.PrintObserver[T]()  // debug: prints all events
observer := ro.NoopObserver[T]()   // discard all events

// Subscription lifecycle
sub := observable.Subscribe(observer)
sub.Wait()          // block until complete or error
sub.Unsubscribe()   // cancel and cleanup
sub.IsActive()      // check if still running
sub.GetError()      // get terminal error

Scheduling

OperatorPurpose
SubscribeOn[T](bufferSize int)Run subscription on async scheduler
ObserveOn[T](bufferSize int)Deliver notifications on async scheduler

Concurrency Modes

// Safe (default): synchronized emissions
ro.NewObservable[T](fn)
ro.NewSafeObservable[T](fn)

// Unsafe: no synchronization, caller must guarantee single-goroutine access
ro.NewUnsafeObservable[T](fn)

// Eventually safe: allows brief unsynchronized period, then synchronizes
ro.NewEventuallySafeObservable[T](fn)

Requirements and compatibility

Written for: Claude Code, OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Claude Code frontmatter

The author says: Designed for Claude Code, Codex or similar harness, and for projects using Golang.

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
samber
Publisher
Samuel Berthe (Community)
Distributed by
Samuel Berthe
Source
samber/cc-skills-golang · skills/golang-samber-ro · commit bb1d43d
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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